Optimasi Fuzzy C-Means Menggunakan Particle Swarm Optimization Untuk Pengelompokan Kabupaten/Kota Di Pulau Kalimantan (Studi Kasus : Data Indikator Kesejahteraan Rakyat Tahun 2020)

Febriyanti, Nur Afifah
Goejantoro, Rito
Prangga, Surya

Eksponensial
Vol 14 No 1 (2023)

Fuzzy C-Means (FCM) is a method of grouping data based on the degree of membership whose observation object is based on the information found in the data describing the object. The FCM method has weaknesses in the initial cluster center determination, so it can be overcome by the Particle Swarm Optimization (PSO) method that can be applied to find the optimal solution of the optimal cluster center determination. The purpose of this research is to determine the optimal number of clusters based on the validity indexes of Partition Coefficient (PC) and Modified Partition Coefficient (MPC), and obtain the results of grouping regencies/cities using the FCMPSO method. Based on the FCMPSO method with a validity index of PC and MPC, it produces an optimal cluster of two clusters, the first cluster consisting of 33 regencies/cities on Kalimantan Island and the second cluster consisting of 23 regencies/cities on Kalimantan Island.